Analytics Vidhya

NOVEMBER 24, 2023

Introduction Convolutional Neural Networks (CNNs) have been key players in understanding images and patterns, transforming the landscape of deep learning. The journey began with Yan introducing the LeNet architecture, and today, we have a range of CNNs to choose from.

Deep Learning 316

Deep Learning Analytics 316

CIO Business Intelligence

MAY 22, 2025

Developing a robust technical architecture for digital twins necessitates a comprehensive understanding of several foundational components and integration of advanced technologies. This architecture allows for better decision-making, predictive maintenance and enhanced operational efficiency. Digital model.

Enterprise 112

Enterprise Visualization Key Performance Indicator Machine Learning 112

Analytics Vidhya

JUNE 5, 2023

By leveraging its unique architecture and memory retention capabilities, LSTM offers an innovative approach to understand the house rent prediction patterns with extraordinary precision. Introduction Long Short Term Memory (LSTM) is a type of deep learning system that anticipates property leases.

Deep Learning 306

Deep Learning Marketing Analytics IT 306

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. But first, let’s define the data mesh design pattern. The past decades of enterprise data platform architectures can be summarized in 69 words. See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

O'Reilly on Data

FEBRUARY 18, 2020

Software architecture, infrastructure, and operations are each changing rapidly. The shift to cloud native design is transforming both software architecture and infrastructure and operations. It’s possible that microservices architecture is hastening the move to other languages (such as Go, Rust, and Python) for web properties.

Data-driven 363

Data-driven Software Statistics Marketing 363

CIO Business Intelligence

NOVEMBER 27, 2024

Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.

Data Architecture 128

Data Architecture Cost-Benefit Machine Learning Experimentation 128

O'Reilly on Data

APRIL 25, 2023

It describes the architecture, goals, and design guidelines; it also tells ChatGPT explicitly not to generate any code. They also describe how the components should be implemented, the architectural pattern to use, the different types of model that are needed, and the tests that ChatGPT must write. His first prompt is very long.

Testing 371

Testing Software Strategy Enterprise 371

AWS Big Data

NOVEMBER 22, 2024

With the dbt adapter for Athena adapter now supported in dbt Cloud, you can seamlessly integrate your AWS data architecture with dbt Cloud, taking advantage of the scalability and performance of Athena to simplify and scale your data workflows efficiently.

Data Lake 103

Data Lake Data Warehouse Cost-Benefit Data Transformation 103

DataKitchen

AUGUST 5, 2021

In our last post, we summarized the thinking behind the data mesh design pattern. In this post (2 of 5), we will review some of the ideas behind data mesh, take a functional look at data mesh and discuss some of the challenges of decentralized enterprise architectures like data mesh. Data Mesh Architecture Example.

Enterprise 246

Enterprise Management Data Processing Analytics 246

DataKitchen

AUGUST 19, 2021

Below is our fourth post (4 of 5) on combining data mesh with DataOps to foster innovation while addressing the challenges of a decentralized architecture. DataKitchen has extensive experience using the data mesh design pattern with pharmaceutical company data. . Figure 3: Example DataOps architecture based on the DataKitchen Platform.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

CIO Business Intelligence

JANUARY 7, 2025

It prevents vendor lock-in, gives a lever for strong negotiation, enables business flexibility in strategy execution owing to complicated architecture or regional limitations in terms of security and legal compliance if and when they rise and promotes portability from an application architecture perspective.

Optimization 98

Optimization Strategy Cost-Benefit Enterprise 98

CIO Business Intelligence

MAY 22, 2025

The new protocols will enable IT teams to seamlessly connect diverse AI agents and to reduce the cost and complexity of AI integrations, adds Gary Lerhaupt, vice president of product architecture at Salesforce. This unlocks new levels of interoperability, reuse, and scale.

Experimentation 129

Experimentation Modeling Cost-Benefit Interactive 129

CIO Business Intelligence

APRIL 8, 2025

We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems. Fragmented systems, inconsistent definitions, outdated architecture and manual processes contribute to a silent erosion of trust in data. The patterns are consistent across industries.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

AWS Big Data

NOVEMBER 7, 2024

The Analyzer provides detailed assessments of the complexity and requirements for the migration, and the Converter automates the actual code conversion process, using pattern-based customizable rules to streamline the transition. The Converter allows developers to customize the conversion patterns for more complex transformations.

Data Warehouse 105

Data Warehouse Reporting Big Data Data Lake 105

Rocket-Powered Data Science

FEBRUARY 15, 2023

These “easy buttons” are: Pattern Detection (D2D), Pattern Recognition (D2ID), Pattern Exploration (D2NBA), and Pattern Exploitation (D2V). Suggestion: take a look at MACH architecture.) Remember to Keep it Simple and Smart (the “KISS” principle ). Test early and often. Expect continuous improvement.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

O'Reilly on Data

NOVEMBER 19, 2024

What’s old becomes new again: Substitute the term “notebook” with “blackboard” and “graph-based agent” with “control shell” to return to the blackboard system architectures for AI from the 1970s–1980s. See the Hearsay-II project , BB1 , and lots of papers by Barbara Hayes-Roth and colleagues. Does GraphRAG improve results?

Unstructured Data 321

Unstructured Data Structured Data Statistics Modeling 321

Rocket-Powered Data Science

JULY 6, 2021

Customer purchase patterns, supply chain, inventory, and logistics represent just a few domains where we see new and emergent behaviors, responses, and outcomes represented in our data and in our predictive models. 5) The emergence of Edge-to-Cloud architectures clearly began pushing Industry 4.0 will look like).

Machine Learning 279

Machine Learning Data-driven Deep Learning IoT 279

AWS Big Data

OCTOBER 29, 2024

The architecture is shown in the following figure. The BMW CDH follows a decentralized, multi-account architecture to foster agility, scalability, and accountability. To address this, Lake Formation offers a hybrid access mode to facilitate a gradual transition to FGAC without disrupting existing data access patterns.

Data Lake 107

Data Lake Sales Metadata Machine Learning 107

CIO Business Intelligence

MAY 21, 2025

Just as cloud computing led to the emergence of software-defined (SD) load balancing, the artificial intelligence (AI) revolution is taking us a step farther, to AI-defined architectures. Additionally, enterprise AI applications are almost exclusively built on Kubernetes with a microservices architecture.

Software 71

Software Enterprise Measurement Management 71

CIO Business Intelligence

DECEMBER 11, 2024

We are now deciphering rules from patterns in data, embedding business knowledge into ML models, and soon, AI agents will leverage this data to make decisions on behalf of companies. Not my original quote, but a cardinal sin of cloud-native data architecture is copying data from one location to another.

Management 111

Management Data Governance Data Science Reporting 111

DataKitchen

APRIL 28, 2021

Whenever a new technology or architecture gains momentum, vendors hijack it for their own marketing purposes. Data fabrics are best regarded as an architecture or design concept, not a specific set of tools. The term fabric gets its name from an architectural approach that provides full point-to-point connectivity between nodes.

Statistics 246

Statistics Optimization Data Analytics Technology 246

CIO Business Intelligence

JANUARY 9, 2025

What began with chatbots and simple automation tools is developing into something far more powerful AI systems that are deeply integrated into software architectures and influence everything from backend processes to user interfaces. An overview. This makes their wide range of capabilities usable.

Software 128

Software Enterprise Key Performance Indicator Machine Learning 128

CIO Business Intelligence

MAY 21, 2025

Different use cases demand different data, models and architectures. Look at your data The success of any AI model largely depends on its ability to understand the language patterns, context and nuances of your business data. Here are four steps to help you get started: 1. Doing so requires human influence.

Metrics 90

Metrics Data Quality Enterprise ROI 90

AWS Big Data

DECEMBER 19, 2024

The proposed solution involves creating a custom subscription workflow that uses the event-driven architecture of Amazon DataZone. The solution architecture is shown in the following screenshot. For Rule type , select Rule with an event pattern. This approach streamlines data access while ensuring proper governance. Choose Next.

Publishing 96

Publishing Unstructured Data Metadata Data-driven 96

DataKitchen

AUGUST 9, 2021

Below is our third post (3 of 5) on combining data mesh with DataOps to foster greater innovation while addressing the challenges of a decentralized architecture. Implementing a data mesh does not require you to throw away your existing architecture and start over. Data mesh does not replace or require any of these.

Testing 246

Testing Data Lake Metadata Publishing 246

AWS Big Data

NOVEMBER 11, 2024

This decoupling provides advantages over traditional architectures. When paired with Kinesis Data Streams, OpenSearch Ingestion allows for sophisticated real-time analytics of data, and helps reduce the undifferentiated heavy lifting of creating a real-time search and analytics architecture.

Metadata 121

Metadata Metrics Analytics Data Processing 121

AWS Big Data

NOVEMBER 11, 2024

In Disaster Recovery (DR) Architecture on AWS, Part I: Strategies for Recovery in the Cloud , we introduced four major strategies for disaster recovery (DR) on AWS. The following diagram illustrates the architecture in the event of a disaster. These strategies enable you to prepare for and recover from a disaster.

Snapshot 110

Snapshot Strategy Dashboards Data Lake 110

AWS Big Data

APRIL 3, 2024

They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions. The following architecture diagram provides a high-level overview of this pattern.

Data Lake 126

Data Lake Snapshot Metadata Data Architecture 126

AWS Big Data

DECEMBER 17, 2024

These improvements enhanced price-performance, enabled data lakehouse architectures by blurring the boundaries between data lakes and data warehouses, simplified ingestion and accelerated near real-time analytics, and incorporated generative AI capabilities to build natural language-based applications and boost user productivity.

Data Lake 98

Data Lake Data Warehouse Data-driven Optimization 98

Rocket-Powered Data Science

MAY 21, 2024

Pure Storage empowers enterprise AI with advanced data storage technologies and validated reference architectures for emerging generative AI use cases. A Data Platform for AI Data is the fuel for AI, because AI devours data—finding patterns in data that drive insights, decisions, and action. Summary AI devours data.

Cost-Benefit 239

Cost-Benefit Unstructured Data Enterprise Technology 239

AWS Big Data

JANUARY 30, 2025

Our approach The migration initiative consisted of two main parts: building the new architecture and migrating data pipelines from the existing tool to the new architecture. Often, we would work on both in parallel, testing one component of the architecture while developing another at the same time.

Data Warehouse 54

Data Warehouse Data Architecture Machine Learning Data Transformation 54

O'Reilly on Data

OCTOBER 19, 2021

Cloud-based data warehouses, such as Snowflake , AWS’ portfolio of databases like RDS, Redshift or Aurora , or an S3-based data lake , are a great match to ML use cases since they tend to be much more scalable than traditional databases, both in terms of the data set sizes as well as query patterns. Software Architecture.

IT 364

IT Testing Experimentation Software 364

AWS Big Data

OCTOBER 19, 2023

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Depending on your use case, it’s common to have a copy of the data between your data lake and data warehouse to support different access patterns. We call this pattern dual writes.

Data Lake 137

Data Lake Data Warehouse Visualization Snapshot 137

AWS Big Data

FEBRUARY 27, 2023

This blog discusses various data sharing options and common architecture patterns that organizations can adopt to set up their data sharing infrastructure based on AWS service availability and data compliance. In the following sections, we discuss each pattern in more detail.

Enterprise 118

Enterprise Publishing Data Lake Management 118

Rocket-Powered Data Science

MARCH 20, 2023

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. We live in a data-rich, insights-rich, and content-rich world.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Machine Learning 325

AWS Big Data

NOVEMBER 7, 2024

Amazon Q generative SQL for Amazon Redshift uses generative AI to analyze user intent, query patterns, and schema metadata to identify common SQL query patterns directly within Amazon Redshift, accelerating the query authoring process for users and reducing the time required to derive actionable data insights.

Metadata 105

Metadata Sales Data Warehouse Optimization 105